Introduction
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The COVID-19 pandemic has given rise to speculations regarding the prices of property in Melbourne. Many have speculated about a Melbourne “housing price bubble” that will soon burst, causing a decline in housing prices. Others have speculated that prices for Australian property will continue to grow. The motivation of this report is to discuss in-depth the level of price volatility of property in Melbourne with attention to many variables such as location, property attributes and time.
Missing data
Missing data in Regions
Missing data in council areas
Question 1
What is the relationship between property distance from the CBD and price?
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Distance-price relationship
Distance-price relationship faceted by region
Number of properties sold in each region
Average distance-price relationshiop
Interactive plot
Question 2
Which regions and council areas have the most expensive housing in Melbourne?
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Average price across regions over time
Spread in property prices
Proportion of average property prices
Proportion of house price according to council area
Top 5 most expensive Council Areas
Grouped by type of property
Price-landsize-rooms relationship
Interactive
Question 3
What is the regression model used to predict the value of property?
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Price relationship with variables Rooms, Bathroom, Landsize
# A tibble: 4 × 5
term estimate std.error statistic p.value
<chr> <dbl> <dbl> <dbl> <dbl>
1 (Intercept) -64493. 11914. -5.41 6.26e- 8
2 Rooms 262913. 4857. 54.1 0
3 Bathroom 251011. 6663. 37.7 2.03e-301
4 Landsize 2.95 1.18 2.51 1.20e- 2Single linear regression model Price ~ Room
Single linear regression model Price ~ Bathroom
Single linear regression model Price ~ Landsize
Question 4
How do the key variables contribute differently to the price of the property in different suburbs?
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Regression
# A tibble: 7 × 5
term estimate std.error statistic p.value
<chr> <dbl> <dbl> <dbl> <dbl>
1 (Intercept) 3977541. 844301. 4.71 0.00000367
2 Rooms 245567. 76404. 3.21 0.00144
3 Bedroom2 74071. 79013. 0.937 0.349
4 Bathroom 73737. 34398. 2.14 0.0328
5 Landsize 13.9 27.0 0.516 0.606
6 YearBuilt -2024. 429. -4.72 0.00000353
7 Distance NA NA NA NA # A tibble: 8 × 5
term estimate std.error statistic p.value
<chr> <dbl> <dbl> <dbl> <dbl>
1 (Intercept) 9544036. 1774648. 5.38 0.000000145
2 Rooms 433736. 109717. 3.95 0.0000949
3 Bedroom2 63477. 110292. 0.576 0.565
4 Bathroom 291676. 50889. 5.73 0.0000000229
5 Landsize -2.52 9.17 -0.275 0.784
6 YearBuilt -5294. 879. -6.02 0.00000000469
7 Distance 132282. 86415. 1.53 0.127
8 Car 46570. 41093. 1.13 0.258 Final regressions
# A tibble: 4 × 5
term estimate std.error statistic p.value
<chr> <dbl> <dbl> <dbl> <dbl>
1 (Intercept) 4020637. 834932. 4.82 2.25e- 6
2 Rooms 315413. 19799. 15.9 1.25e-42
3 Bathroom 81373. 33500. 2.43 1.57e- 2
4 YearBuilt -2044. 424. -4.82 2.19e- 6# A tibble: 4 × 5
term estimate std.error statistic p.value
<chr> <dbl> <dbl> <dbl> <dbl>
1 (Intercept) 9754083. 1669210. 5.84 1.24e- 8
2 Rooms 500103. 37537. 13.3 1.30e-32
3 Bathroom 310430. 49352. 6.29 1.02e- 9
4 YearBuilt -5181. 838. -6.18 1.93e- 9Linear regression for Brunswick
Linear regressions for South Yarra
Residuals
Regression equations
\[\widehat{\text{Price}} = 4020637 + 315413~\text{Rooms}+ 81373~\text{Bathroom}- 2044~\text{YearBuilt}\]
\[\widehat{\text{Price}} = 9754082 + 500103~\text{Rooms}+ 310429~\text{Bathroom}- 5180~\text{YearBuilt}\]
Question 5
Which suburb and region provided the most houses for different classes of families?, with classes being: Lower class, Middle Class and Upper Class
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Lower class region
[1] 188
Lower class suburb
Middle class region
[1] 12774
Middle class suburb
Upper class region
[1] 8859
Upper class suburb
Conclusion
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Property price tends to increase with a decrease from the distance from the Melbourne CBD. However, other location variables such as council area and region seemed to have a larger impact on property pricing.
The most expensive region, in terms of housing, is the Southern Metropolitan while Boroondara, which is in that same region, is the most expensive council area.
We found how the number of rooms, bathrooms, and Year built have different impacts on the price of house in Melbourne and particularly how they have different impacts on price in Brunswick and South Yarra
We concluded that the region and suburb that sold the most houses for lower-class families were Western Metropolitan and Footscray. For middle-class families, they were Northern Metropolitan and Reservior. Finally, for upper-class families, they were Southern Metropolitan and Glen Iris.